Correlation Between IShares China and SPDR MSCI
Can any of the company-specific risk be diversified away by investing in both IShares China and SPDR MSCI at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining IShares China and SPDR MSCI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between iShares China CNY and SPDR MSCI World, you can compare the effects of market volatilities on IShares China and SPDR MSCI and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in IShares China with a short position of SPDR MSCI. Check out your portfolio center. Please also check ongoing floating volatility patterns of IShares China and SPDR MSCI.
Diversification Opportunities for IShares China and SPDR MSCI
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between IShares and SPDR is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding iShares China CNY and SPDR MSCI World in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SPDR MSCI World and IShares China is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on iShares China CNY are associated (or correlated) with SPDR MSCI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPDR MSCI World has no effect on the direction of IShares China i.e., IShares China and SPDR MSCI go up and down completely randomly.
Pair Corralation between IShares China and SPDR MSCI
Assuming the 90 days trading horizon IShares China is expected to generate 4.85 times less return on investment than SPDR MSCI. But when comparing it to its historical volatility, iShares China CNY is 6.6 times less risky than SPDR MSCI. It trades about 0.29 of its potential returns per unit of risk. SPDR MSCI World is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest 6,588 in SPDR MSCI World on August 29, 2024 and sell it today you would earn a total of 342.00 from holding SPDR MSCI World or generate 5.19% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
iShares China CNY vs. SPDR MSCI World
Performance |
| Timeline |
| iShares China CNY |
| SPDR MSCI World |
IShares China and SPDR MSCI Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with IShares China and SPDR MSCI
The main advantage of trading using opposite IShares China and SPDR MSCI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IShares China position performs unexpectedly, SPDR MSCI can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in SPDR MSCI will offset losses from the drop in SPDR MSCI's long position.| IShares China vs. iShares III Public | IShares China vs. iShares Core MSCI | IShares China vs. iShares France Govt | IShares China vs. iShares Edge MSCI |
| SPDR MSCI vs. SPDR MSCI World | SPDR MSCI vs. SPDR SP Dividend | SPDR MSCI vs. SPDR SP 500 | SPDR MSCI vs. SPDR BB SB |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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